Data Augmentation aims to enlarge the train set using transformations. Conventional image transformations include cropping, flips, rotation and etc.
Recent studies consider employing multiple images for augmentation. MixUp [1]} proposes to combine the pixel values and labels of two images by linear interpolation. It has been proven effective for the classification task, which is followed by [2]}.
Our method employ the idea of instance mixtures with task-specific designs. Concretely, we achieve the mixture operation on two snippets within a video rather than on two different videos likewise MixUp, making the perturbations to snippets more controllable for incorporating the proposed method into the existing WS-TAL frameworks.
